Digital video capabilities can be incorporated into a wide range of devices, including digital televisions, digital direct broadcast systems, wireless communication devices such as radio telephone handsets, wireless broadcast systems, personal digital assistants (PDAs), laptop or desktop computers, digital cameras, digital recording devices, video gaming devices, video game consoles, and the like. Digital video devices implement video compression techniques, such as MPEG-2, MPEG-4, or ITU-T H.264/MPEG-4, Part 10, Advanced Video Coding (AVC), to transmit and receive digital video more efficiently. Video compression techniques perform spatial and temporal prediction to reduce or remove redundancy inherent in video sequences.
Block-based video compression techniques may perform spatial prediction and/or temporal prediction. Intra-coding relies on spatial prediction to reduce or remove spatial redundancy between video blocks within a given coded unit, which may comprise a video frame, a slice of a video frame, or the like. In contrast, inter-coding relies on temporal prediction to reduce or remove temporal redundancy between video blocks of successive coded units of a video sequence. For intra-coding, a video encoder performs spatial prediction to compress data based on other data within the same coded unit. For inter-coding, the video encoder performs motion estimation and motion compensation to track the movement of corresponding video blocks of two or more adjacent coded units.
A coded video block may be represented by prediction information that can be used to create or identify a predictive block, and a residual block of data indicative of differences between the block being coded and the predictive block. In the case of inter-coding, one or more motion vectors are used to identify the predictive block of data from a previous or subsequent coded unit, while in the case of intra-coding, the prediction mode can be used to generate the predictive block based on data within the coded unit associated with the video block being coded. Both intra-coding and inter-coding may define several different prediction modes, which may define different block sizes and/or prediction techniques used in the coding. Additional types of syntax elements may also be included as part of encoded video data in order to control or define the coding techniques or parameters used in the coding process.
After block-based prediction coding, the video encoder may apply transform, quantization and entropy coding processes to further reduce the bit rate associated with communication of a residual block. Transform techniques may comprise discrete cosine transforms (DCTs) or conceptually similar processes, such as wavelet transforms, integer transforms, or other types of transforms. In a discrete cosine transform process, as an example, the transform process converts a set of pixel values into transform coefficients, which may represent the energy of the pixel values in the frequency domain. Quantization is applied to the transform coefficients, and generally involves a process that limits the number of bits associated with any given transform coefficient. Entropy coding comprises one or more processes that collectively compress a sequence of quantized transform coefficients.
Filtering of video blocks may be applied as part of the encoding and decoding loops, or as part of a post-filtering process on reconstructed video blocks. Filtering is commonly used, for example, to reduce blockiness or other artifacts common to block-based video coding. Filter coefficients (sometimes called filter taps) may be defined or selected in order to promote desirable levels of video block filtering that can reduce blockiness and/or improve the video quality in other ways. A set of filter coefficients, for example, may define how filtering is applied along edges of video blocks or other locations within video blocks. Different filter coefficients may cause different levels of filtering with respect to different pixels of the video blocks. Filtering, for example, may smooth or sharpen differences in intensity of adjacent pixel values in order to help eliminate unwanted artifacts.